1. Field of the Invention
This invention relates generally to the composition (creation), execution (delivery), and monitoring (measurement) of context-based, customized service bundles over computer networks. More specifically, this invention relates to user context based distributed self service system with decision support capabilities.
2. Background Art
Prior systems for service purchase decision support and delivery, including those multi-attribute systems for purchasing support, make use of available simple historical and current user data and demographic data, and/or extensive profiles completed by the user to provide personalization. They do not, however, develop user contexts based on adaptive algorithms and supervised and unsupervised learning sub-processes and do not include the use of affective data. Prior systems also do not support the real time configuration, comparison and selection of service packages, do not make use of visual decision support tools and do not provide for the real time management of the services bundle during execution.
Current systems generally focus on purchase decision support and are developed for a single domain such as a telephone system or car radio and the functionalities and interfaces learned by the user cannot be generalized to similar services purchase and execution tasks in other domains. Some of the systems have been developed specifically for push functionality and use a specific type of interaction with the user such as interactive questioning via an expert system.
Other systems which make use of Bayesian Network data mining techniques make use of adaptive algorithms and supervised learning but do not make use of the variety of historical, contextual and affective data and do not apply the predictive models to purchasing decision support in various domains.
Web usage mining tools analyze web traffic and sales data for two purposes: (1) system and network performance analysis (for performance optimization), and (2) marketing and merchandising (product assortment, web design, cross-sells, and up-sells, email promotion, portal advertisements, referral services). Web mining tools are used to categorize and segment users and to provide personalized services to users and collaborative filtering is widely used by retailers.
Other systems use dynamic pricing but provide only forward (seller initiated) auctions as opposed to reverse (buyer initiated) auctions. Other systems using auctions for dynamic pricing do not allow auctions based on a bundling of services from different providers.
While OLAP (Online Analytical Processing) capabilities built on top of relational database management systems provide decision support capabilities including multi-dimensional data models (also known as star schema) and exploratory analysis capability through pivot, roll-up, and drill-down operations for different dimensions, they, along with visual decision support tools, do not provide extensive capabilities of the Absolute tool. They do not provide confirmatory analysis, what-if analysis, and iterative, undirected exploratory analysis.